This review paper focuses on the neonatal brain segmentation algorithms in the literature. It provides an overview of clinical magnetic resonance imaging (MRI) of the newborn brain and the challenges in automated tissue classification of neonatal brain MRI. It presents a complete survey of the existing segmentation methods and their salient features. The different approaches are categorized into intracranial and brain tissue segmentation algorithms based on their level of tissue classification. Further, the brain tissue segmentation techniques are grouped based on their atlas usage into atlas-based, augmented atlas-based and atlas-free methods. In addition, the research gaps and lacunae in literature are also identified.