Probing is a technique used to analyze and interpret the internal representations and mechanisms of machine learning models, particularly neural networks, by examining how well certain properties or tasks can be predicted from the model's intermediate layers. It helps in understanding what information is captured by the model and how it is organized, providing insights into the model's interpretability and biases.