Reinforcement Learning stands apart from other machine learning techniques due to its focus on decision-making through interaction. While supervised learning relies on labeled data to train algorithms and unsupervised learning seeks patterns in data without explicit labels, RL is a dynamic process. Agents in RL learn from trial and error, continuously adjusting their strategies based on the feedback they receive from their environment.