Natural Language Processing (NLP) is an essential component of AI that enables computers to understand, interpret, and generate human language. Despite its importance across various fields, including education and healthcare, NLP for African languages remains underexplored due to linguistic diversity and limited resources. We conducted a theoretical analysis of existing NLP datasets and resources available for African languages spoken in Morocco. We also reviewed recent literature to identify gaps and potential areas of improvement. A significant finding is that while there are limited studies on NLP for Moroccan African languages, the proportion of these languages that require specialized training data ranges from 30% to 45%. This highlights the need for more tailored resources. Our study underscores the critical role of localized and specialized NLP tools in enhancing communication and education within Morocco's diverse linguistic landscape. We recommend increased investment in research into African language NLP, with a focus on developing robust training datasets and supporting interdisciplinary collaborations between linguists and computer scientists. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.