Definition
No-Free-Lunch Theorem
The No-Free-Lunch Theorem is a theoretical result in machine learning and optimisation. It states that, when averaged over all possible problems, no single learning algorithm consistently outperforms any other.
This implies there is no universal master algorithm that is the best choice for every predictive task.