### Description

Airflow has connections:
```
Amazon Web Services
Amazon Redshift
Elastic MapReduce
```

It wasn't easy to find the `Elastic MapReduce` because it wasn't listed as Amazon.
I think it would be better to rename it to `Amazon Elastic MapReduce` for easier find in the Connections droplist

### Use case/motivation

_No response_

### Related issues

_No response_

### Are you willing to submit a PR?

- [ ] Yes I am willing to submit a PR!

### Code of Conduct

- [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

airflow/providers/amazon/aws/hooks/emr.py
super().__init__(client_type="emr-containers", *args, **kwargs)  
        self.virtual_cluster_id = virtual_cluster_id
    def submit_job(
        self,
        name: str,
        execution_role_arn: str,
        release_label: str,
        job_driver: dict,
        configuration_overrides: Optional[dict] = None,
        client_request_token: Optional[str] = None,
    ) -> str:
        """
        Submit a job to the EMR Containers API and and return the job ID.
        A job run is a unit of work, such as a Spark jar, PySpark script,
        or SparkSQL query, that you submit to Amazon EMR on EKS.
        See: https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/emr-containers.html#EMRContainers.Client.start_job_run  # noqa: E501
        :param name: The name of the job run.
        :type name: str
        :param execution_role_arn: The IAM role ARN associated with the job run.
        :type execution_role_arn: str
        :param release_label: The Amazon EMR release version to use for the job run.
        :type release_label: str
        :param job_driver: Job configuration details, e.g. the Spark job parameters.