The increasing integration of machine learning (ML) systems into critical decision-making processes necessitates a distinct exploration of fairness, especially within diverse sociocultural contexts. This paper examines the philosophical foundation of fairness in Machine Learning through an African lens, emphasizing the unique ethical, historical, and cultural dimensions that shape its interpretation and application across the continent. Unlike the Euro-Western paradigms that often prioritize individual rights or utilitarian principles, African philosophy, particularly the concept of Ubuntu, emphasizes communal well-being, interconnectedness and restorative justice. These principles provide a distinctive framework for addressing systemic biases and inequities embedded in Machine Learning systems. The paper also explores the broader philosophical underpinnings of fairness in African ethics, including the prioritization of holistic approaches and moral economy. These perspectives advocate for Machine Learning systems that consider the collective good, minimize harm and promote equity in access and outcomes. Furthermore, the African emphasis on pluralism and diversity underscores the need for adaptable fairness frameworks that respect local contexts while contributing to global Machine Learning ethics discourse. An African perspective on fairness therefore offers valuable insights for the global AI community.