Some of the challenges in pattern recognition include dealing with high dimensional data where traditional methods may fail due to the 'curse of dimensionality.' Noise and distortion in data can also create significant challenges in recognizing patterns accurately. Furthermore, the need for large amounts of labeled data for supervised pattern recognition can also be a limiting factor. Lastly, ensuring the model's robustness to variations in patterns while avoiding overfitting is a significant challenge.