A value function is a crucial component in reinforcement learning, representing the expected return or future rewards an agent can achieve from a given state or state-action pair. It guides the agent's decision-making process by evaluating the long-term benefits of various actions, enabling it to learn optimal policies for maximizing cumulative rewards.