Clause learning is a technique used in artificial intelligence and computer science to improve the efficiency of solving problems, particularly in satisfiability (SAT) problems. It involves analyzing conflicts that arise during problem-solving and generating new clauses, or rules, that prevent the same mistakes from happening again. This helps the algorithm to avoid redundant searches and speeds up the overall process. By incorporating these learned clauses into its reasoning, the algorithm can make more informed decisions in future iterations. This method enhances the performance of SAT solvers and other related systems, making them more effective in finding solutions to complex problems.