Reinforcement learning is fully general. NNs on their own can only do prediction. You can predict what object is in an image, or what word a person will say next, etc. And that is quite powerful, and there are a lot of useful things you can do with that ability.
But there are also a lot of things you can't do. Really any task that requires performing a series of actions to reach some kind of goal. Which covers most of the things we want AI to do. Like controlling a robot, playing a game, talking to a human, proving a theorem, etc.
Of course with regular ML, you could do mimicry, and predict what actions a human would do at every time step. But then you are severly limited by the time and quality of your training data. RL requires no training data and can potentially learn to be much better than humans.
But there are also a lot of things you can't do. Really any task that requires performing a series of actions to reach some kind of goal. Which covers most of the things we want AI to do. Like controlling a robot, playing a game, talking to a human, proving a theorem, etc.
Of course with regular ML, you could do mimicry, and predict what actions a human would do at every time step. But then you are severly limited by the time and quality of your training data. RL requires no training data and can potentially learn to be much better than humans.