Convolution operation is a mathematical technique used in signal processing and deep learning to combine two functions, often used to extract features from data by applying a filter to an input signal. It involves sliding a kernel over an input to produce a feature map, and is fundamental in the functioning of convolutional neural networks (CNNs) for tasks like image and speech recognition.