Orthogonal decomposition is a method in linear algebra and functional analysis where a vector space is divided into mutually orthogonal subspaces, allowing for simplified analysis and computation. This technique is crucial in various applications such as signal processing, quantum mechanics, and numerical analysis, where it aids in breaking down complex problems into more manageable components.