Style transfer is a technique in machine learning that involves reimagining an image by applying the stylistic elements of one image (the style image) to the content of another image (the content image), effectively separating and recombining content and style. This process leverages convolutional neural networks to extract and blend features from both images, allowing for creative transformations such as turning a photograph into a painting in the style of a famous artist.