Fully Convolutional Networks (FCNs) are a type of deep learning architecture designed for tasks where input and output have spatial correspondence, such as image segmentation. Unlike traditional convolutional networks, FCNs replace fully connected layers with convolutional layers, allowing them to handle inputs of varying sizes and produce outputs of corresponding dimensions.