Adaptive Quadrature is a numerical integration technique that improves the accuracy of approximating the area under a curve. It works by dividing the integration interval into smaller segments and adjusting the size of these segments based on the function's behavior. If the function changes rapidly in a region, the method uses more subdivisions there, while using fewer subdivisions in smoother areas. This approach contrasts with traditional quadrature methods, which use fixed intervals. By focusing computational effort where it is most needed, Adaptive Quadrature can achieve higher precision with fewer calculations, making it efficient for complex functions often encountered in fields like mathematics and engineering.