Reinforcement Learning from Human Feedback combines RL with human evaluation to align AI outputs with human preferences and values. In this approach, humans rate or rank model outputs, and these evaluations guide the learning process. RLHF has been instrumental in making large language models more aligned, safe, and user-friendly. For enterprises, RLHF enables fine-tuning of AI systems based on real-world usage and expectations.