Experience Replay is a mechanism in reinforcement learning where past transitions (state, action, reward, next state) are stored in a memory buffer. The agent then samples mini-batches randomly from this buffer to break correlation and improve learning stability. This is a core feature in Deep Q-Networks (DQN).