Reinforcement learning is all about gamifying the learning process.
This type of machine learning uses a reward-penalty method to teach an AI system. If it makes the right move, it gets rewarded. If it makes a mistake, it receives a penalty.
In other words, reinforcement learning forces a system to learn and adapt quickly, or it otherwise loses serious numerical rewards. It's a feedback-based machine learning method in which the AI agent learns to (rightly) behave in an environment by taking actions and seeing those actions' results.
In short, the agent learns from experience without any pre-programming and doesn't require any human supervision.
