What is the purpose of the hypothesis in the scientific method?

To validate an experiments methods and results by allowing independent labs to create a repeatable experiment and achieve the same results.

To provide scientific street cred.

The hypothesis is your formal idea about how something works. The formal experimental and/or theoretical work you do is in some views your best shot(s) at EITHER disproving that idea and then reformulating a newer hypothesis OR providing evidence which supports all or parts of your original hypothesis and again reformulating(or abandoning) your original hypothesis and starting the cycle over again. I’ve always liked Poppers approach. He says one can only absolutely disprove an idea/hypothesis. One could always provide what are called trivial tests to support an idea and misleadingly give false life to the idea/hypothesis.

Hypothesis is there to articulate what is being examined it actually serves to protect against bias.

Also, you often end up proving your hypothesis was false for one reason or another.

Along the same lines as what @virtualist said, you can only disprove, never prove. So the most rigorous way to approach the answer to a scientific question is to present a series of hypotheses and subject them to experiments that have the potential to disprove them, and keep the ones that survive, narrowing the possibilities, eventually down to one. You can’t just accumulate data which will suddenly spell out a definite answer.

Experiments generally are driven by a larger question. A hypothesis is introduced to make the experiment subject to statistical hypothesis testing.

Every experiment actually has two hypotheses: the null hypothesis and the alternative hypothesis. The null hypothesis is the default position that there is no relationship between the two things you’re looking at, and the alternative hypothesis is that there is some relationship between them.

When you do a statistical test, you set some threshold that allows you to reject the null hypothesis (so all you are really saying is that it is statistically unlikely that no relationship exists between the two things you’re looking at).

A good experiment is designed with appropriate blinds so that the experimenter cannot bias the outcome of the experiment.

I think you might have the wrong idea as to what a hypothesis is. A hypothesis is not an expectation of what facts will pop up. It’s an explanation that ties existing facts together in a consistent way and makes predictions for the facts we don’t have yet.
A question as to the outcome of an experiment would be a fundamentally different kind of thing from a hypothesis. In fact, researchers work with both.

With that said, hypotheses are important because they are the actual answers to the questions we want answered. Nobody gives a dayum about the facts on their own, they only become interesting when they can tell us which of several competing explanations is most likely to be the right one.

Commonplace example:
Known facts: my nose is runny, I have a headache and my stomach hurts.
Problem: What’s the matter with me?
Hypothesis: I have a fever.
Testable prediction: If this is true, my body temperature is a few degrees Celsius over 37 right now.
(Experimental question: What is my temperature?)
Experiment: Sticking a thermometer somewhere and measuring my body temperature.

Now, if we didn’t have a hypothesis, knowing my body temperature wouldn’t help much. I would just know that my nose is runny, I have a headache, my stomach hurts and my temperature is elevated. This is not an explanation of what’s going on with my body. The facts on themselves cannot solve the problem unless they are connected by means of a hypothesis.

You have to know what you are testing for. A properly run experiment is supposed to do everything possible to try to eliminate bias or any influence other than the one being tested for. Hence, the use of controls and double blind testing. It is also why it is expected that experimental results can be duplicated by other researchers. The null hypothesis is the working assumption and only if the evidence overwhelmingly points to positive results is the null hypothesis rejected.

Without a hypothesis there can be no question.

I always think it’s a point of reference (that you believe is right) against which you can compare the reality, It lets the audience know where you were coming from before you started the experiment.