Instruction Tuning is a crucial fine-tuning process where a model is adjusted to better understand and adhere to human instructions. By providing diverse tasks with explicit instructions during training, the model learns to generalize and apply the instructions across various tasks. This process enhances the model's ability to respond effectively to specific commands, improving its practical usability in conversational and assistance scenarios like virtual assistants.