Reinforcement Learning is an area of Machine Learning that deals with algorithms that learn from their environment by taking actions and observing the rewards they receive for those actions. Unlike supervised learning, which uses labeled data to learn from, reinforcement learning algorithms learn from their environment and the feedback they receive from it. This feedback is used to adjust their behavior to maximize the rewards they receive.