One Shot Prompting is a method where you provide a machine learning model with only one example or instruction, aiming for the model to generalize and apply this knowledge to similar unseen tasks. It contrasts with approaches requiring many examples. One Shot Prompting is particularly useful in scenarios where data collection is challenging. It's related to Few Shot Learning, which uses a few instances, and Zero Shot Learning, where no examples are provided.