Big Data and machine learning are not two comparable concepts; rather they are complementary concepts which work together to define and implement machine learning systems. Big Data refers to the large chunk of unstructured data which is collected from various systems such as transaction data, customer data, business data etc. Machine Learning is the technique used to enable machines and systems to self-learn rather than the user coding all the business logic. Machine learning algorithms refers to the Big Data to derive useful trends & patterns so as to create automated incomes to specific use-cases.
Machine learning models require data as an input to them, sometimes the larger the data the better are the results of machine learning model. In such situation big data is fed as an input to machine learning model to produce desired output.
Basically big data can be one of the input source for machine learning model.
For eg: A recommender system is a machine learning model to give recommendation on products on ecommerce sites. When amazon shows popular items it is machine learning output of big data of purchases of other users and your purchase data.