Nonlinear detection involves identifying signals or patterns in data that do not adhere to a simple linear relationship, often requiring advanced algorithms and models to accurately interpret complex interactions. This is crucial in fields like communications, finance, and machine learning, where real-world data often exhibits nonlinear characteristics that linear models fail to capture effectively.