Languages get used because they cover specific use cases or libraries.
UNIX -> C
Browser -> JavaScript
Data Science -> Python, R, Julia, Chapel, C++
Windows Development -> .NET languages, C and C++
Android -> Java, Kotlin, C and C++
macOS, iOS, tvOS, watchOS -> Objective-C, Swift, C and C++
Docker, Kubernetes -> Go
Game development -> Assembly, C, C++ and C#
High performance data switches -> Erlang
Of course one is free to use outlier languages and try to bend them into specific use cases, but then one also has to live with less tooling as the ones that are the "platform language" for the specific use case.
Throughout my career I always kept an open mind to try out new programming languages and paradigms, but in what concerns production code I learned the hard way to only use the official platform languages.