Few-shot learning models frequently achieve comparable or better accuracy than traditional machine learning models, particularly in scenarios with limited labelled data. This feature enhances Few-Shot Learning's ability to provide better results from small training sets, which makes it useful in tasks such as image recognition where labelled data is scarce.