Statistics. Why we never "accept" the null hypothesis

So this question has been bugging me, this is my answer and all I got was a "why not?" marked in red at the end.

"We never accept the null because our goal is to reject it. With sufficient evidence we are able to reject it, with not enough evidence we fail to reject it, which is not the same as accepting it. "

So am I missing something?

It is because to accept the null would to lock yourself into a definite answer. When failing to reject the null, it just means that the stated alternative is incorrect and not that the null is correct. There are three types of alternative hypotheses and so when one is wrong it does not make them all wrong.

Because you've only got two outcomes. Either the null hypothesis is rejected or accepted. If it is not rejected then it must be accepted. It sounds like you're relying on a nonexistent grey area in your argument.