State abstraction is a technique in reinforcement learning and artificial intelligence that simplifies complex environments by reducing the number of states an agent must consider, thereby improving learning efficiency and decision-making. It involves grouping similar states together based on certain criteria, allowing the agent to generalize from past experiences and focus on more relevant information.