Local search is a metaheuristic and algorithmic paradigm for solving computational problems, particularly optimization problems, by iteratively improving a candidate solution. It investigates the solution space by iteratively moving from a current candidate solution to a neighboring one defined by a specific neighborhood structure. Key characteristics include its iterative nature, reliance on local moves, and the potential to converge to local optima. Its significance stems from its effectiveness in exploring large search spaces for finding approximate or exact solutions when exhaustive search is impractical.