 No free lunch theorem

The No Free Lunch (NFL) theorem is a concept in optimization and machine learning that states that there is no one-size-fits-all algorithm that is guaranteed to perform well on all possible problems. Instead, the performance of optimization algorithms is problem-dependent, meaning that an algorithm that works well for one class of problems may perform poorly on another.