A convolutional layer is a fundamental building block of convolutional neural networks (CNNs). It applies a set of filters to the input data to produce a feature map, highlighting important features like edges and shapes. This operation is key in image processing tasks. For instance, it helps to detect patterns within images by translating the data into a structured hierarchy of features, which is a core advantage of CNNs.