Population-based search is an optimization technique that explores a search space by maintaining and evolving a set of potential solutions, rather than a single solution, to find an optimal or near-optimal solution. It is widely used in complex problem domains where the search space is large and not well understood, leveraging diversity among solutions to avoid local optima and improve convergence speed.