Using machine learning (ML) approach, we unearthed a new III-V semiconducting material having an optimal bandgap for high-efficient photovoltaics with the chemical composition of Gallium-Boron-Phosphide (GaBP2, space group: Pna2(1)). ML predictions are further validated by state-of-the-art ab initio density functional theory simulations. The stoichiometric Heyd-Scuseria-Ernzerhof bandgap of GaBP2 is noted to be 1.65 eV, a close ideal value (1.4-1.5 eV) to reach the theoretical Queisser-Shockley limit. The calculated electron mobility is similar to that of silicon. Unlike perovskites, the newly discovered material is thermally, dynamically and mechanically stable. Above all the chemical composition of GaBP2 is non-toxic and relatively earth abundant, making it a new generation of PV material. Using ML, we showed that with a minimal set of features, the bandgap of III-III-V and II-IV-V semiconductor can be predicted up to an RMSE of less than 0.4 eV. We have presented a set of scaling laws, which can be used to estimate the bandgap of new III-III-V and IIIV-V semiconductor, with three different crystal phases, within an RMSE of approximate to 0.4 eV.