An Evolutionary Algorithm is a type of optimization technique inspired by the process of natural selection. It mimics biological evolution by generating a population of potential solutions to a problem, which then undergoes selection, mutation, and crossover to produce new generations of solutions. The goal is to improve the quality of solutions over time, similar to how species evolve in nature. These algorithms are commonly used in fields like artificial intelligence, machine learning, and operations research. They are particularly effective for complex problems where traditional methods may struggle, as they explore a wide solution space and can adapt to changing conditions.