Text line extraction serves as a critical preprocessing stage in optical character recognition (OCR) systems, significantly influencing the accuracy of subsequent text recognition tasks. While extensive research has been conducted globally on text line segmentation for Latin-based scripts, Indic scripts present unique challenges due to their complex writing structures, presence of vowel modifiers, conjunct characters, and varying baseline orientations. In this paper, we present a comprehensive review of the research efforts published in the last five years, specifically focusing on text line extraction techniques developed exclusively for Indic scripts and languages. The survey highlights methodologies applied to scripts such as Devanagari, Gujarati, Tamil, Telugu, Bengali, and other widely used Indian languages, with an emphasis on ongoing research trends in India. By systematically analyzing algorithmic approaches, dataset availability, evaluation metrics, and script-specific challenges, this review aims to consolidate current knowledge and identify research gaps, thereby guiding future advancements in text recognition for Indic language technologies.