Food biodiversity is essential for improving nutrition and reducing hunger in populations worldwide. However, in middle and low-income countries, the biodiversity of food production does not necessarily represent food consumption patterns by population. We used Brazil, one of the world's megabiodiverse countries, as a case study to investigate the following questions: what is the prevalence of consumption of biodiverse foods in Brazil, and what are the socioeconomic factors that influence their consumption throughout the country? We used data from a Brazilian representative national dietary survey to estimate the frequency of food consumption of unconventional food plants, edible mushrooms, and wild meat, in according to socioeconomic variables. Thus, we investigated the socioeconomic predictors of Unconventional Food Plants consumption using methods of Machine Learning (ML) and multiple zero-inflated Poisson (ZIP) regression. We showed that biodiverse food consumption in Brazil is low, just related by 1.3% of the population, varying in according to area, ethnicity, age, food insecurity, sex, and educational level. Our findings of low utilization of biodiversity suggest an important mismatch between the rich biodiversity of the country and its representation in the human diet.